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Telecommunications Industry AssociationTR-30.3/08-12-017 Lake Buena Vista, FL December 8 - 9, 2008. v1.0 - 20050426. TIA921B Algorithm – An Update Alan Clark. Interfering Source Model. Packet. Parameters: p12, p21 = Transition probabilities (forward) - PowerPoint PPT Presentation

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v1.0 - 20050426

Document Cover Sheet

Project Number PN-3-0062-RV2

Document Title TIA921B Algorithm – An Update

Source Telchemy

Contact Name: Alan Clark Complete Address: 2905 Premiere Parkway, Suite 280 Duluth, GA 30097

Phone: +1-678-387-3000 Fax: +1-678-387-3008 Email: alan.d.clark@telchemy.com

Distribution TR-30.3

For Incorporation Into TIA Publication X For Information

Intended Purpose of Document (Select one) Other (describe) -

The document to which this cover statement is attached is submitted to a Formulating Group or sub-element thereof of the Telecommunications Industry Association (TIA) in accordance with the provisions of Sections 6.4.1–6.4.6 inclusive of the TIA Engineering Manual dated March 2005, all of which provisions are hereby incorporated by reference.

Abstract

TIA921B Algorithm – An Update

Telecommunications Industry Association TR-30.3/08-12-017Lake Buena Vista, FL December 8 - 9, 2008

TIA921B Algorithm – An Update

Alan Clark

Interfering Source Model

2

1No packets

Packet Parameters:- p12, p21 = Transition probabilities (forward)- p12, p21 = Transition probabilities (reverse)- k = MM update frequency

Low value of k, low value of p21 … e.g. VoIP

High value of k, high value of p21 … e.g. TCP

Interfering Source Model

• Model reverse flow– TCP – assume model generates primary packet

stream• estimate packet volume in reverse direction for normal

ACKs

– VoIP – assume symmetric packet flow– IPTV – assume unidirectional packet flow

Base Model - 1

EstimatedQueuing

Delay

InterferingSource

InterferingSource

Stream

Limits for queuing delay in each directionAND common delay (i.e. shared queue)

Overflow model (i.e. queue length limit)

LossModel

Base Model - 2

At time t:For each interfering source

Probability of being in packet burst = p(b)Decide on a packet burst lengthDecide on the position within the packet burstCompute contribution that preceding part of packet

burst added to queuing delay

Issue 1

If next “t” is close to previous then both events could have occurredin the same packet burst

Add:if t within previous estimate of packet burst length then

use previously calculated burst parameters

Issue 2

If multiple test stream packets are closely spaced they will add to the queuing delay (i.e. self congestion)

Add:incorporate contribution of this packet to queuing delay

Model

+ QueueLimit

InterferingSourceInterfering

SourceInterferingSourceInterfering

Source

TestStream

+ QueueLimit

InterferingSource

InterferingSource

InterferingSource

InterferingSource

TestStream

Model

+ QueueLimit

InterferingSource

InterferingSource

InterferingSource

InterferingSource

TestStream

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